Forest parameter includes forest stand scale parameter and single-tree scale parameter, emergence of remote sensing technologies brings technical innovation to extraction of forest parameters, and by combining aerial photographs with fieldwork investigation, manual labor and time can be greatly saved. Ordinary optical remote sensing is easily influenced by factors such as illumination, atmosphere, observation angles, and only two-dimensional information can be acquired, so that application range is limited. Light Detection and Ranging (LiDAR) is an emerging active three-dimensional remote sensing technology, which can simultaneously acquire horizontal distribution and vertical structure information of a forest canopy surface and further can acquire forest parameters of the forest stand scale and provide forest parameters of the single-tree scale based on high-density LiDAR point cloud data.
Single-tree segmentation needs to be performed firstly while forest parameters of the single-tree scale are acquired based on point cloud data. At present, a single-tree segmentation method in general use is a segmentation method based on raster images. However, precision of such a segmentation method depends on a resolution ratio of the raster images to a great extent, and precision of the point cloud data in an aspect of a vertical structure is lost in the process of transforming point cloud into raster, so that segmentation effect is not ideal.